방법 증거 기록

Natural Language Generation

Natural Language Generation (NLG) is the branch of natural language processing that automatically produces fluent, human-readable text from structured data, knowledge graphs, or semantic representations. Formalised in the classical pipeline by Reiter and Dale (2000) and surveyed comprehensively by Gatt and Krahmer (2018), NLG powers applications ranging from automated financial reporting and weather bulletins to data storytelling and conversational agents.

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원본 기록

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Natural Language Generation (NLG)

분류학적 방법 기록 · process-pipeline / text-mining

Gatt, A. & Krahmer, E. (2018). Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation. Journal of Artificial Intelligence Research, 61, 65-170. · URL
Reiter, E. & Dale, R. (2000). Building Natural Language Generation Systems. Cambridge University Press. · ISBN 9780521620369

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Same method familyAutomatic Text Evaluationmachine-suggested · Relational suggestion, not evidence.See alsoGPT Fine-Tuningmachine-suggested · Relational suggestion, not evidence.Same method familyMachine Translationmachine-suggested · Relational suggestion, not evidence.Same method familyRetrieval-Augmented Generationmachine-suggested · Relational suggestion, not evidence.See alsoSequence-to-Sequence Modelmachine-suggested · Relational suggestion, not evidence.Same method familyText Summarizationmachine-suggested · Relational suggestion, not evidence.See alsoTransformermachine-suggested · Relational suggestion, not evidence.